PERPUSTAKAAN DATA : SEBUAH PENGAMAT TERHADAP UNIVERSITY OF TORONTO MAP AND DATA LIBRARY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Data libraries have been widely known in Europe and America. The fact that these libraries have been optimized for upporting research makes it significant for Indonesia to initiate the development data libraries. However, Indonesian language literature on this specific type of library is still very limited. Although some of data library aspects have been considerably implemented, the author has not found any data library exist in Indonesia. Therefore, this paper is aimed at defining a representative data library by looking at the University of Toronto Map and Digital Library, as one of data libraries, and observing its facilities. The author will attempt to make a basic observation and description in regard. It is expected that the results will be useful as a reference for developing data libraries in Indonesia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.014 |
| Open science | 0.015 | 0.023 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it